AI Business is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them. Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 3099067.

Finance

Gartner names ‘cool vendors’ in AI for banking, investment services

by Chuck Martin
Article Image

Four companies are making waves in the hotly contested market

Banking and investment businesses are increasingly turning to AI software to optimize their operations, and a recent report from Gartner shines a light on several vendors providing this tech.

The majority (53%) of financial institutions are employing AI methods to foster new thinking and disrupt business models, the firm said, as it identified four tech suppliers as ‘Cool Vendors in AI for Banking and Investment Services.’

Who is who

The Cool Vendors “offer solutions that target direct capital market and asset management operations or solutions that can enhance delivery of products and services to the customers,” according to Gartner.

They leverage AI technologies, such as deep learning, natural language processing and predictive analytics with the goal of reducing cost, increasing revenue or improving customer experience.

Such AI solutions can help with risk management, optimizing operations and improving decision making.

For example, Socure uses machine learning to improve risk management by analyzing information from thousands of disparate data sources in real time.

“By utilizing advanced data science and machine learning techniques, we are able to improve the overall identity verification performance and user experience,” said Tom Thimot, CEO of Socure, which is in use by more than 200 banks, lenders and payment providers globally.

Eigen Technologies, another ‘cool vendor,’ uses its natural language platform to provide clients with self-service data extraction and analysis. The platform aims to help organizations improve operational efficiency by using the banks’ internal data.

Axyon AI’s products focus on benchmarking, managing risk and meeting positive client returns. The company leverages deep learning for client support in asset management and capital markets.

The fourth 'cool vendor,' Tenspace, analyzes social media using AI-based tools to improve decision making for three scenarios: credit scoring, lending, and anti-money laundering.

Artificial intelligence and machine learning were ranked as the top game-changing technologies in financial services, according to the 2020 Gartner CIO Survey.

Following AI (27%) were data analytics (26%), cloud computing (24%), APIs (18%), digital transformation (14%) and operation process technologies (8%).

Back in 2019, Gartner’s AI in Organizations survey found that the majority (56%) of financial services executives saw AI as a way to optimize their current processes.

Gartner has published its Cool Vendor research since 2004 across nearly 100 different market areas, including retail, data science and analytics, typically highlighting lesser-known, emerging vendors. The criteria for naming the ‘cool’ companies, nominated by Gartner analysts, includes being innovative, impactful and intriguing.

Gartner makes three recommendations for banking and investment services looking to deploy AI-based tools for their business:

  • Include AI adoption and innovation into the IT investment strategy, no matter the size of the organization;
  • Partner with manage service providers or system integrators that have a client base in banking;
  • Evaluate the disruptive vendors’ techniques and test scenarios to determine potential impact on routine operations.

Gartner does not officially endorse its ‘cool vendors,’ and always adds a disclaimer about evaluating their fitness for a particular purpose. But, if nothing else, the ‘cool vendors’ earn serious bragging rights.

Practitioner Portal - for AI practitioners

Story

UK's ICO publishes guidance on AI and data protection

8/3/2020

The document aims to help organizations mitigate the risks of using personal data in AI applications

Story

Perfect AI model, broken app: Integration patterns and testing needs

7/24/2020

It is a long way from having a working machine learning model on a local laptop to having a full-fledged fashion store with a mobile app incorporating this model

Practitioner Portal

EBooks

More EBooks

Upcoming Webinars

More Webinars

Experts in AI

Partner Perspectives

content from our sponsors

Research Reports

9/30/2019
More Research Reports

Infographics

AI tops the list of most impactful emerging technologies

Infographics archive

Newsletter Sign Up


Sign Up